Journal of Advanced Research (Jun 2023)

Dualistic classification of high grade serous ovarian carcinoma has its root in spatial heterogeneity

  • Tingting Sun,
  • Zuwei Zhang,
  • Liming Tian,
  • Yu Zheng,
  • Linxiang Wu,
  • Yunyun Guo,
  • Xiaohui Li,
  • Yuanyuan Li,
  • Hongwei Shen,
  • Yingrong Lai,
  • Junfeng Liu,
  • Huanhuan Cui,
  • Shasha He,
  • Yufeng Ren,
  • Guofen Yang

Journal volume & issue
Vol. 48
pp. 213 – 225

Abstract

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Introduction: Widespread intra-peritoneal metastases is a main feature of high grade serous ovarian carcinoma (HGSOC). Recently, the extent of tumour heterogeneity was used to evaluate the cancer genomes among multi-regions in HGSOC. However, there is no consensus on the effect of tumour heterogeneity on the evolution of the tumour metastasis process in HGSOC. Objectives: We performed whole-exome sequencing in multiple regions of matched primary and metastatic HGSOC specimens to reveal the genetic mechanisms of ovarian tumourigenesis and malignant progression. Methods: 63 samples (including ovarian carcinoma, omentum metastasis, and normal tissues) were used. We analyzed the genomic heterogeneity, traced the subclone dissemination and establishment history and compared the different genetic characters of cancer evolutionary models in HGSOC. Results: We found that HGSOC had substantial intra-tumour heterogeneity (median 54.2, range 0 ∼ 106.7), high inter-patient heterogeneity (P < 0.001), but relatively limited intra-patient heterogeneity (P = 0.949). Two COSMIC mutational signatures were identified in HGSOCs: signature 3 was related to homologous recombination, and signature 1 was associated with aging. Two scenarios were identified by phylogenetic reconstruction in our study: 3 cases (33.3 %) showed star topology, and the other 6 cases (66.7 %) displayed tree topology. Compared with star topology group, more driver events were identified in tree topology group (P < 0.001), and occurred more frequently in early stage than in late stage of clonal evolution (P < 0.001). Moreover, compared with the star topology group, the tree topology group showed higher rate of intra-tumour heterogeneity (P = 0.045). Conclusion: A dualistic classification model was proposed for the classification of HGSOC based on spatial heterogeneity, which may contribute to better managing patients and providing individual treatment for HGSOC patients.

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